ODSC - Open Data Science

NOVEMBER 19, 2024

ODSC West 2024 showcased a wide range of talks and workshops from leading data science, AI, and machine learning experts. This blog highlights some of the most impactful AI slides from the world’s best data science instructors, focusing on cutting-edge advancements in AI, data modeling, and deployment strategies.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Tableau 102

Tableau Business Intelligence Business Intelligence Analytics 102

AWS Machine Learning Blog

MAY 31, 2024

Challenges associated with these stages involve not knowing all touchpoints where data is persisted, maintaining a data pre-processing pipeline for document chunking, choosing a chunking strategy, vector database, and indexing strategy, generating embeddings, and any manual steps to purge data from vector stores and keep it in sync with source data.

AWS 126

AWS Machine Learning Machine Learning Database 126

Pickl AI

APRIL 10, 2023

The starting range for a SQL Data Analyst is $61,128 per annum. How SQL Important in Data Analytics? Sincerely, SQL is used by Data Analysts for storing data in a particular type of Database and ensures flexibility in accessing or updating data. An SQL Data Analyst is vital for an organisation.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

ODSC - Open Data Science

MAY 10, 2023

Although tabular data are less commonly required to be labeled, his other points apply, as tabular data, more often than not, contains errors, is messy, and is restricted by volume. One might say that tabular data modeling is the original data-centric AI!

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

Pickl AI

MARCH 4, 2024

How do you load data into Power BI? Loading data into Power BI is a straightforward process. Using Power Query, users can connect to various data sources such as Excel files, SQL databases, or cloud services like Azure. Once connected, data can be transformed and loaded into Power BI for analysis.

Power BI 52

Power BI Data Analysis Data Analysis Data Models 52

The MLOps Blog

JUNE 27, 2023

See also Thoughtworks’s guide to Evaluating MLOps Platforms End-to-end MLOps platforms End-to-end MLOps platforms provide a unified ecosystem that streamlines the entire ML workflow, from data preparation and model development to deployment and monitoring. Dolt Dolt is an open-source relational database system built on Git.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

phData

SEPTEMBER 25, 2024

Under this category, tools with pre-built connectors for popular data sources and visual tools for data transformation are better choices. Integration: How well does the tool integrate with your existing infrastructure, databases, cloud platforms, and analytics tools? What is Fivetran?

ETL 52

ETL Database Data Warehouse Analytics 52

Pickl AI

JUNE 23, 2023

Data Collection The process begins with the collection of relevant and diverse data from various sources. This can include structured data (e.g., databases, spreadsheets) as well as unstructured data (e.g., Data Preparation Once collected, the data needs to be preprocessed and prepared for analysis.

AI 52

AI AI Data Governance Data Quality 52

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Tableau 52

Tableau Business Intelligence Business Intelligence Analytics 52

Pickl AI

NOVEMBER 18, 2024

Key Features of Power BI Power BI offers a range of powerful features that enhance its utility in Data Analysis and Visualisation. One of its core strengths is data integration, allowing users to connect to various data sources, including databases, cloud services, and spreadsheets.

Power BI 52

Power BI Tableau Data Analysis Data Analysis 52

Pickl AI

NOVEMBER 28, 2024

Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data. Model evaluation and tuning involve several techniques to assess and optimise model accuracy and reliability. databases, CSV files).

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

APRIL 21, 2024

You need to make that model available to the end users, monitor it, and retrain it for better performance if needed. Microsoft Azure ML Provided by Microsoft , Azure Machine Learning (ML) is a cloud-based machine learning platform that enables data scientists and developers to build, train, and deploy machine learning models at scale.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Mlearning.ai

NOVEMBER 29, 2023

GP has intrinsic advantages in data modeling, given its construction in the framework of Bayesian hierarchical modeling and no requirement for a priori information of function forms in Bayesian reference. Decision Trees ML-based decision trees are used to classify items (products) in the database.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

It simplifies feature access for model training and inference, significantly reducing the time and complexity involved in managing data pipelines. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

AWS 112

AWS Machine Learning Machine Learning ML 112

The Data Administration Newsletter

FEBRUARY 19, 2025

Data often arrives from multiple sources in inconsistent forms, including duplicate entries from CRM systems, incomplete spreadsheet records, and mismatched naming conventions across databases. These issues slow analysis pipelines and demand time-consuming cleanup.

Data Preparation 52

Data Preparation Machine Learning Machine Learning Database 52